I'll present two new concepts in deep learning and show how
we used them to achieve a significant improvement in stereo
matching, which is one of the most fundamental problems in
computer vision. The first is a new residual architecture
dedicated for metric learning, and the second is a general way
to assess the confidence in the network's prediction.

*Amit is a deep learning and computer vision engineer at Magic Leap and
M.Sc student in deep learning and computer vision at CS-TAU